1. Field of the Invention
One or more embodiments of the present invention relate to a system, medium, and method calibrating gray data, and more particularly, to a system, medium, and method calibrating gray data in which gray data included in the color gamut of a source device is calibrated, thereby removing a color tone that can appear when the gray data is reproduced in a reproduction device, for more consistent high quality color between devices.
2. Description of the Related Art
Color calibration has been referred to as a process of adjusting an output visual characteristic of a display to fit a reference color of another device, and is widely used in order to accurately represent colors for printing. Since video monitors use a red, green, and blue (RGB) rendering method to display different colors, in order to print an image using cyan, magenta, yellow, and black (CMYK) ink, through a CMYK rendering method, color calibration of the image is performed. For color calibration, color lookup table values are conventionally used.
Meanwhile, color input and output devices reproducing colors, such as a monitor, a scanner, a camera, or a printer, use different color spaces or color models according to their application field. For example, in the case of a color image, printing devices use a CMY or CMYK color space, and color cathode ray tube (CRT) monitors or computer graphic devices use an RGB color space. Devices required to separately process color, saturation and brightness use a hue, saturation, and intensity (HIS) color space. Further, in order to define device-independent colors, that is, colors that can be accurately reproduced by any device, a Commission Internationale de L'Eclairage (CIE) color space has also been used, and leading examples of the CIE color space include CIEXYZ, CIELab, and CIELuv color spaces. In addition to these color spaces, the range of colors that can be represented, that is, color gamuts, may be different between color input and output devices. Due to the difference between these color gamuts, when an identical image is observed through different input and output devices, the observed images may be observed to have different colors.
The CIELab color model is based on the color model that the Commission Internationale de L'Eclairage (CIE) originally suggested as an international standard for measuring colors. Here, the CIELab color space is device-independent. That is, irrespective of device, such as a monitor, printer, or computer, which is used to generate or output an image, constant observable color can be generated across the devices. A CIELab color is formed with a lightness (L) component and two color tones a and b. The color tone component a is positioned between green and red, and the component b is positioned between blue and yellow.
Meanwhile, starting from Windows Vista color space, color spaces supported by Microsoft include a CIELab color space, and a CIECAM02 color space, which is used in color matching. The CIECAM02 color space, which is an extended version of the CIELab color space system, is capable of accurately modeling the human visual characteristic with observation environments reflected thereon. More specifically, in a conventional color management system (CMS) of an operating system (OS), an observation light has been fixed to the known D50 when color matching between a display and a printer is performed. However, in Windows Vista, the CIECAM02 color space is supported, thereby allowing comparison and observation of images under a variety of illumination conditions, including the known D65, F, and A light sources, as well as the D50 light source.
However, as an example, when the CIECAM02 color space is used and gray data of a source device is reproduced in a reproducing device, a color tone may appear.
FIG. 1 illustrates a conventional method of calibrating gray data.
This conventional method of calibrating gray data depends mostly on the human visual characteristic and user interaction. As illustrated in FIG. 1, first, a gray test patch 12 with a predetermined lightness level is displayed on the screen. Then, based upon user interaction it can be determined whether a color tone is seen in the displayed test patch 12, a gray balance guide map 14 on the bottom left hand corner of the screen and a gray balance cursor 16 can be adjusted, thereby removing an observed color tone. For example, if a red tone is seen in the test patch 12, the gray balance cursor 16 is moved in the red direction of the gray balance guide map 14, thereby removing the red color tone in the test patch 12.
However, since this method depends on the human visual characteristic and human interaction, calibration results may differ depending on each individual evaluator's subjectivity, which may often be inconsistent and inaccurate.